Healthcare Risk Adjustment And Predictive Modeling
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Healthcare Risk Adjustment And Predictive Modeling
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Author : Ian G. Duncan
language : en
Publisher: ACTEX Publications
Release Date : 2011
Healthcare Risk Adjustment And Predictive Modeling written by Ian G. Duncan and has been published by ACTEX Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Business & Economics categories.
This text is listed on the Course of Reading for SOA Fellowship study in the Group & Health specialty track. Healthcare Risk Adjustment and Predictive Modeling provides a comprehensive guide to healthcare actuaries and other professionals interested in healthcare data analytics, risk adjustment and predictive modeling. The book first introduces the topic with discussions of health risk, available data, clinical identification algorithms for diagnostic grouping and the use of grouper models. The second part of the book presents the concept of data mining and some of the common approaches used by modelers. The third and final section covers a number of predictive modeling and risk adjustment case-studies, with examples from Medicaid, Medicare, disability, depression diagnosis and provider reimbursement, as well as the use of predictive modeling and risk adjustment outside the U.S. For readers who wish to experiment with their own models, the book also provides access to a test dataset.
Risk Adjustment For Measuring Health Care Outcomes
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Author : Lisa I. Iezzoni
language : en
Publisher: Asociation of University Programs in Health Administration/Health Administration Press
Release Date : 2013
Risk Adjustment For Measuring Health Care Outcomes written by Lisa I. Iezzoni and has been published by Asociation of University Programs in Health Administration/Health Administration Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Decision making categories.
This text offers independent chapters for a multidisciplinary readership of students and professionals in areas such as biostatistics, public health, psychology, and health policy. It introduces concepts and methods for designing, using, and evaluating risk adjustment methods when comparing outcomes of care such as costs, clinical outcomes, and patient-centered outcomes in various health care settings. Because the field is broad and changing, the book does not review existing risk adjustment methods; instead, it concentrates on basic methods and principles that apply generally to risk adjustment. Individual chapters are devoted to data from administrative sources, medical records, and patient surveys. Later chapters cover practical issues in developing and evaluating risk adjustment methods and understanding their validity and reliability. There is also material on risk adjustment for specific populations. This fourth edition contains a new chapter on using risk adjustment in the management of health care organizations, plus new information on genetic, social, and environmental risk factors. This edition reflects current practice in electronic health records and health information technologies. Iezzoni teaches medicine at Harvard Medical School. Annotation ©2012 Book News, Inc., Portland, OR (booknews.com).
Actionable Intelligence In Healthcare
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Author : Jay Liebowitz
language : en
Publisher: CRC Press
Release Date : 2017-04-07
Actionable Intelligence In Healthcare written by Jay Liebowitz and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-07 with Business & Economics categories.
This book shows healthcare professionals how to turn data points into meaningful knowledge upon which they can take effective action. Actionable intelligence can take many forms, from informing health policymakers on effective strategies for the population to providing direct and predictive insights on patients to healthcare providers so they can achieve positive outcomes. It can assist those performing clinical research where relevant statistical methods are applied to both identify the efficacy of treatments and improve clinical trial design. It also benefits healthcare data standards groups through which pertinent data governance policies are implemented to ensure quality data are obtained, measured, and evaluated for the benefit of all involved. Although the obvious constant thread among all of these important healthcare use cases of actionable intelligence is the data at hand, such data in and of itself merely represents one element of the full structure of healthcare data analytics. This book examines the structure for turning data into actionable knowledge and discusses: The importance of establishing research questions Data collection policies and data governance Principle-centered data analytics to transform data into information Understanding the "why" of classified causes and effects Narratives and visualizations to inform all interested parties Actionable Intelligence in Healthcare is an important examination of how proper healthcare-related questions should be formulated, how relevant data must be transformed to associated information, and how the processing of information relates to knowledge. It indicates to clinicians and researchers why this relative knowledge is meaningful and how best to apply such newfound understanding for the betterment of all.
Managing And Evaluating Healthcare Intervention Programs
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Author : Ian Duncan, FSA, FIA, FCIA, MAAA
language : en
Publisher: ACTEX Publications
Release Date : 2014-01-20
Managing And Evaluating Healthcare Intervention Programs written by Ian Duncan, FSA, FIA, FCIA, MAAA and has been published by ACTEX Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-20 with Business & Economics categories.
Since its publication in 2008, Managing and Evaluating Healthcare Intervention Programs has become the premier textbook for actuaries and other healthcare professionals interested in the financial performance of healthcare interventions. The second edition updates the prior text with discussion of new programs and outcomes such as ACOs, Bundled Payments and Medication Management, together with new chapters that include Opportunity Analysis, Clinical Foundations, Measurement of Clinical Quality, and use of Propensity Matching.
The Health Care Data Guide
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Author : Lloyd P. Provost
language : en
Publisher: John Wiley & Sons
Release Date : 2022-06-15
The Health Care Data Guide written by Lloyd P. Provost and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-15 with Medical categories.
An Essential text on transforming raw data into concrete health care improvements Now in its second edition, The Health Care Data Guide: Learning from Data for Improvement delivers a practical blueprint for using available data to improve healthcare outcomes. In the book, a team of distinguished authors explores how health care practitioners, researchers, and other professionals can confidently plan and implement health care enhancements and changes, all while ensuring those changes actually constitute an improvement. This book is the perfect companion resource to The Improvement Guide: A Practical Approach to Enhancing Organizational Peformance, Second Edition, and offers fulsome discussions of how to use data to test, adapt, implement, and scale positive organizational change. The Health Care Data Guide: Learning from Data for Improvement, Second Edition provides: Easy to use strategies for learning more readily from existing health care data Clear guidance on the most useful graph for different types of data used in health care A step-by-step method for making use of highly aggregated data for improvement Examples of using patient-level data in care Multiple methods for making use of patient and other feedback data A vastly better way to view data for executive leadership Solutions for working with rare events data, seasonality and other pesky issues Use of improvement methods with epidemic data Improvement case studies using data for learning A must read resource for those committed to improving health care including allied health professionals in all aspects of health care, physicians, managers, health care leaders, and researchers.
Healthcare S Out Sick Predicting A Cure Solutions That Work
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Author : Gary D. Miner
language : en
Publisher: CRC Press
Release Date : 2019-01-04
Healthcare S Out Sick Predicting A Cure Solutions That Work written by Gary D. Miner and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-04 with Medical categories.
The U.S. healthcare system is in "complete chaos-disarray." Medical costs have increased significantly over the past 6 years with 70% increase for deductibles and 24% or more for health insurance premiums. All the while, workers earnings have either not increased or if they did, the pay raises were for less than the increase in the cost of medical care. The situation is unsustainable and the public wants the system fixed. This book offers ways of fixing the problems in healthcare. HEALTHCARE's OUT SICK - PREDICTING A CURE - Solutions that WORK !!!! first defines the "healthcare in crisis" problem. Through real patient experiences, the book describes the difficulties of getting through the maze of complexity among the plethora of "silo providers" which make up the industry. The heart of the book provides readers with a comprehensive solution that can work, a disruption that is necessary to provide Americans the medical care they need without the US public and healthcare providers and payors going into bankruptcy, insolvency or closure. This book delves into digitized medicine, payor and provider reimbursement models, and value-based healthcare delivery. It also includes a philosophy or mode of thinking and operation for the solutions that are needed for diagnosis-effective, cost-effective, and time-efficient healthcare delivery, of which digitized medicine, value-based care, and payor reimbursement modes are just some of the factors. The authors propose that the real solution involves having the patient at the center of the issues and changing from an archaic gold standard way of thinking to a "Predictive Analytic thinking" where one gets at the real truth by doing "real science" that in the end becomes effective not only for the population but for the individual person. This all leads to real person-centered and person-directed medicine and healthcare delivery.
Health Insurance Across Worldwide Health Systems
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Author : Aida Isabel Tavares
language : en
Publisher: BoD – Books on Demand
Release Date : 2024-03-13
Health Insurance Across Worldwide Health Systems written by Aida Isabel Tavares and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-13 with Medical categories.
Health insurance is the mechanism used to respond to uncertainty and risk aversion to illness. Health insurance, whether private, public, or mixed, serves as the main structural foundation for health systems across countries. Its objectives are to minimize the financial burden of medical expenses on people and to enhance population health. Globally, there is a great diversity of health systems and even greater variation among them. There are substantial differences in health systems and health insurance between low- and middle-income nations. The primary explanation for this could be the disparities in the resources available to fund the health system. High-income countries have the financing ability to fund the provision of health care, whereas low- and medium-income countries have a harder time funding health care. Another challenge health systems face nowadays is the achievement of the United Nations Sustainable Development Goal 3: healthy lives and promoting well-being for all. To create resilient and sustainable health systems that guarantee healthy lives and foster well-being for people of all ages, many countries are redesigning their healthcare systems by improving financing, access, and coverage. This book discusses these issues in different health systems around the world, in low-, middle-, and high-income countries.
Machine Learning And Immersive Technologies For User Centered Digital Healthcare Innovation
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Author : Federico Colecchia
language : en
Publisher: Frontiers Media SA
Release Date : 2025-06-09
Machine Learning And Immersive Technologies For User Centered Digital Healthcare Innovation written by Federico Colecchia and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-09 with Science categories.
Emerging technologies such as machine learning and immersive technologies (including virtual reality and augmented reality) hold great potential for driving disruptive healthcare innovation. However, the adoption of digital technology in healthcare, including use of data-driven tools in support of clinical decision-making and patient-facing applications relying on consumer electronic devices, is often hindered by issues of user experience, trust, equitability, and fairness. There is increasing recognition of a need to facilitate further convergence between the development of emerging technologies and user-centered design research for healthcare, with a view to achieving a positive impact on patients, care professionals, and the healthcare system. This article collection addresses current development trends relating to user-centered digital healthcare innovation based on machine learning and immersive technologies, in order to identify opportunities associated with the deployment of new solutions in a range of environments – including clinical, domestic, and educational settings – and barriers to the adoption of technology by end users. A key aim is to identify opportunities for strengthening interdisciplinary collaboration as well as methods of lowering barriers and overcoming obstacles for the benefit of patients, care professionals, and the healthcare system. Examples of potential outcomes are effective design and use of solutions based on machine learning and immersive technologies to improve user experience, strategies to facilitate ethical development of digital technology for healthcare, and methods of encouraging adoption of advanced tools developed in line with principles of equitability and fairness. Articles should address issues of user-centered digital healthcare innovation driven by machine learning and immersive technologies. Submissions should ideally be positioned at the intersection of digital technology development with user-centered design, although contributions more technical in nature as well as user experience studies are also welcome. A non-exhaustive list of suitable topics and manuscript types is given below: • Machine learning and/or immersive technologies (including augmented reality and virtual reality) for user-centered digital healthcare. • Clinical decision support systems. • Patient-facing applications. • Tools for education and training of future medical professionals. • Potential barriers to adoption of technology: issues of user experience, trust, equitability, and fairness in digital healthcare. • Reviews and contributions discussing the development of intuitive, accessible, and inclusive digital interfaces. • All aspects of healthcare that are being or have the potential to be impacted by machine learning and immersive technologies.
Provider Led Population Health Management
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Author : Richard Hodach
language : en
Publisher: John Wiley & Sons
Release Date : 2016-09-15
Provider Led Population Health Management written by Richard Hodach and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-15 with Health & Fitness categories.
Provider-Led Population Health Management: Key Healthcare Strategies in the Cognitive Era, Second Edition draws connections among the new care-delivery models, the components of population health management, and the types of health IT that are required to support those components. The key concept that ties all of this together is that PHM requires a high degree of automation to reach everyone in a population, engage those patients in self-care, and maximize the chance that they will receive the proper preventive, chronic, and acute care. While this book is intended for healthcare executives and policy experts, anyone who is interested in health care can learn something from its exploration of the major issues that are stirring health care today. In the end, the momentous changes going on in health care will affect us all.
Artificial Intelligence And Machine Learning In Health Care And Medical Sciences
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Author : Gyorgy J. Simon
language : en
Publisher: Springer Nature
Release Date : 2024-03-04
Artificial Intelligence And Machine Learning In Health Care And Medical Sciences written by Gyorgy J. Simon and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-04 with Medical categories.
This open access book provides a detailed review of the latest methods and applications of artificial intelligence (AI) and machine learning (ML) in medicine. With chapters focusing on enabling the reader to develop a thorough understanding of the key concepts in these subject areas along with a range of methods and resulting models that can be utilized to solve healthcare problems, the use of causal and predictive models are comprehensively discussed. Care is taken to systematically describe the concepts to facilitate the reader in developing a thorough conceptual understanding of how different methods and resulting models function and how these relate to their applicability to various issues in health care and medical sciences. Guidance is also given on how to avoid pitfalls that can be encountered on a day-to-day basis and stratify potential clinical risks. Artificial Intelligence and Machine Learning in Health Care and Medical Sciences: Best Practices and Pitfallsis a comprehensive guide to how AI and ML techniques can best be applied in health care. The emphasis placed on how to avoid a variety of pitfalls that can be encountered makes it an indispensable guide for all medical informatics professionals and physicians who utilize these methodologies on a day-to-day basis. Furthermore, this work will be of significant interest to health data scientists, administrators and to students in the health sciences seeking an up-to-date resource on the topic.